منابع مشابه
The Kaplan Meier Estimate in Survival Analysis
The need for analyzing time to event data arises in a number of applied fields, such as epidemiology, public health and medicine [1]. ‘Time to event’ simply means the time from entry into a study until a subject has a particular outcome. The study that involves time to event can be a cohort study on a specific number of patients or participants which should be followed for a particular time per...
متن کاملAbout an adaptively weighted Kaplan-Meier estimate.
The minimum averaged mean squared error nonparametric adaptive weights use data from m possibly different populations to infer about one population of interest. The definition of these weights is based on the properties of the empirical distribution function. We use the Kaplan-Meier estimate to let the weights accommodate right-censored data and use them to define the weighted Kaplan-Meier esti...
متن کاملKaplan–Meier Estimator
The Kaplan–Meier estimator is a nonparametric estimator which may be used to estimate the survival distribution function from censored data. The estimator may be obtained as the limiting case of the classical actuarial (life table) estimator, and it seems to have been first proposed by Böhmer [2]. It was, however, lost sight of by later researchers and not investigated further until the importa...
متن کاملSurvival analysis I: the Kaplan-Meier method.
The Kaplan-Meier (KM) method is used to analyze 'time-to-event' data. The outcome in KM analysis often includes all-cause mortality, but could also include other outcomes such as the occurrence of a cardiovascular event. The purpose of this article is to explain the basic concepts of the KM method, to provide some guidance regarding the presentation of the KM results and to discuss some importa...
متن کاملAsymptotic properties of mean survival estimate based on the Kaplan-Meier curve with an extrapolated tail.
Asymptotic distribution of the mean survival time based on the Kaplan-Meier curve with an extrapolated 'tail' is derived. A closed formula of the variance estimate is provided. Asymptotic properties of the estimator were studied in a simulation study, which showed that this estimator was unbiased with proper coverage probability and followed a normal distribution. An example is used to demonstr...
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ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 1988
ISSN: 0090-5364
DOI: 10.1214/aos/1176351049